sfaR

Maximum likelihood estimation for stochastic frontier analysis (SFA) of production (profit) and cost functions. The package includes the basic stochastic frontier for cross-sectional or pooled data with several distributions for the one-sided error term (i.e., Rayleigh, gamma, Weibull, lognormal, uniform, generalized exponential and truncated skewed Laplace), the latent class stochastic frontier model (LCM) as described in Dakpo et al. (2021) doi:10.1111/1477-9552.12422, for cross-sectional and pooled data, and the sample selection model as described in Greene (2010) doi:10.1007/s11123-009-0159-1, and applied in Dakpo et al. (2021) doi:10.1111/agec.12683. Several possibilities in terms of optimization algorithms are proposed.